{"id":"https://openalex.org/W2058950011","doi":"https://doi.org/10.1109/icacci.2013.6637258","title":"Fractional coefficients of transformed edge palm images with Cosine, Kekre and Slant wavelet transforms for palm print identification","display_name":"Fractional coefficients of transformed edge palm images with Cosine, Kekre and Slant wavelet transforms for palm print identification","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W2058950011","doi":"https://doi.org/10.1109/icacci.2013.6637258","mag":"2058950011"},"language":"en","primary_location":{"id":"doi:10.1109/icacci.2013.6637258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2013.6637258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5028359630","display_name":"Sudeep D. Thepade","orcid":"https://orcid.org/0000-0001-7809-4148"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sudeep D. Thepade","raw_affiliation_strings":["Pimpri Chinchwad College of Engineering, Pune, India","Pimpri Chinchwad Coll. of Eng., Pune, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pimpri Chinchwad College of Engineering, Pune, India","institution_ids":[]},{"raw_affiliation_string":"Pimpri Chinchwad Coll. of Eng., Pune, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027504605","display_name":"Santwana Gudadhe","orcid":"https://orcid.org/0000-0002-9894-854X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Santwana S. Gudadhe","raw_affiliation_strings":["Pimpri Chinchwad College of Engineering, Pune, India","Pimpri Chinchwad Coll. of Eng., Pune, India"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Pimpri Chinchwad College of Engineering, Pune, India","institution_ids":[]},{"raw_affiliation_string":"Pimpri Chinchwad Coll. of Eng., Pune, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"698","last_page":"703"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10828","display_name":"Biometric Identification and Security","score":1.0,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10057","display_name":"Face and Expression Recognition","score":0.9707000255584717,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12357","display_name":"Digital Media Forensic Detection","score":0.9416000247001648,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/palm-print","display_name":"Palm print","score":0.9276354312896729},{"id":"https://openalex.org/keywords/palm","display_name":"Palm","score":0.7460558414459229},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6211220026016235},{"id":"https://openalex.org/keywords/discrete-cosine-transform","display_name":"Discrete cosine transform","score":0.5292113423347473},{"id":"https://openalex.org/keywords/wavelet-transform","display_name":"Wavelet transform","score":0.5122613310813904},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.5044540166854858},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49651581048965454},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.49464866518974304},{"id":"https://openalex.org/keywords/wavelet","display_name":"Wavelet","score":0.4883231818675995},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.48371249437332153},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.45473724603652954},{"id":"https://openalex.org/keywords/canny-edge-detector","display_name":"Canny edge detector","score":0.41156694293022156},{"id":"https://openalex.org/keywords/edge-detection","display_name":"Edge detection","score":0.39515221118927},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.3474843502044678},{"id":"https://openalex.org/keywords/image-processing","display_name":"Image processing","score":0.33274900913238525},{"id":"https://openalex.org/keywords/biometrics","display_name":"Biometrics","score":0.13492277264595032}],"concepts":[{"id":"https://openalex.org/C2777503689","wikidata":"https://www.wikidata.org/wiki/Q7128108","display_name":"Palm print","level":3,"score":0.9276354312896729},{"id":"https://openalex.org/C94598645","wikidata":"https://www.wikidata.org/wiki/Q2347874","display_name":"Palm","level":2,"score":0.7460558414459229},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6211220026016235},{"id":"https://openalex.org/C2221639","wikidata":"https://www.wikidata.org/wiki/Q2877","display_name":"Discrete cosine transform","level":3,"score":0.5292113423347473},{"id":"https://openalex.org/C196216189","wikidata":"https://www.wikidata.org/wiki/Q2867","display_name":"Wavelet transform","level":3,"score":0.5122613310813904},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.5044540166854858},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49651581048965454},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49464866518974304},{"id":"https://openalex.org/C47432892","wikidata":"https://www.wikidata.org/wiki/Q831390","display_name":"Wavelet","level":2,"score":0.4883231818675995},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.48371249437332153},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.45473724603652954},{"id":"https://openalex.org/C14705441","wikidata":"https://www.wikidata.org/wiki/Q597183","display_name":"Canny edge detector","level":5,"score":0.41156694293022156},{"id":"https://openalex.org/C193536780","wikidata":"https://www.wikidata.org/wiki/Q1513153","display_name":"Edge detection","level":4,"score":0.39515221118927},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.3474843502044678},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.33274900913238525},{"id":"https://openalex.org/C184297639","wikidata":"https://www.wikidata.org/wiki/Q177765","display_name":"Biometrics","level":2,"score":0.13492277264595032},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icacci.2013.6637258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icacci.2013.6637258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.44999998807907104,"display_name":"Affordable and clean energy","id":"https://metadata.un.org/sdg/7"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":5,"referenced_works":["https://openalex.org/W1974900975","https://openalex.org/W2039012808","https://openalex.org/W2111410439","https://openalex.org/W2140959843","https://openalex.org/W2161749790"],"related_works":["https://openalex.org/W3135266770","https://openalex.org/W2260048578","https://openalex.org/W79564642","https://openalex.org/W2736294736","https://openalex.org/W2765988996","https://openalex.org/W3169126738","https://openalex.org/W1994279415","https://openalex.org/W2558559991","https://openalex.org/W1986338341","https://openalex.org/W2545065926"],"abstract_inverted_index":{"Paper":[0],"presents":[1],"extended":[2],"performance":[3,161,171],"comparison":[4],"of":[5,14,31,38,51,67,77,89,118,133,146,180],"palm":[6,16,32,53,90,111,135,148,174,188],"print":[7,17,33,91,112,136,149,175,189],"identification":[8,137,176],"techniques":[9],"based":[10],"on":[11,110,142],"fractional":[12,120,178],"coefficients":[13,98,121,179],"transformed":[15,100,181],"edge":[18,54,59,101,113,126,193],"image":[19,68,78,114],"using":[20,57,177],"Cosine,":[21],"Kekre,":[22],"Slant":[23],"transform":[24,63],"and":[25,40,105,115,153,186,197],"respective":[26],"wavelet":[27,107,168],"transforms.":[28],"The":[29,163],"uniqueness":[30],"is":[34,46,80,140,158],"in":[35,49,99,166,173],"the":[36,52,65,85],"pattern":[37,45],"ridges":[39],"furrows":[41],"it":[42],"has.":[43],"This":[44],"considered":[47,159],"here":[48,82],"form":[50],"images":[55,92,150,182],"obtained":[56],"various":[58],"detection":[60,127,194],"methods.":[61],"In":[62,191],"domain,":[64],"energy":[66],"gets":[69],"concentrated":[70],"towards":[71],"low":[72,96],"frequency":[73,97],"region;":[74],"this":[75],"characteristic":[76],"transforms":[79,104,108],"used":[81],"to":[83,201],"reduce":[84],"feature":[86],"vector":[87],"size":[88],"by":[93],"selecting":[94],"these":[95],"images.":[102,190],"Image":[103],"their":[106],"applied":[109],"7":[116],"ways":[117],"taking":[119],"along":[122],"with":[123],"five":[124],"different":[125],"methods":[128],"give":[129],"total":[130],"210":[131],"variation":[132],"proposed":[134],"method.":[138],"Experimentation":[139],"done":[141],"a":[143],"test":[144],"bed":[145],"1000":[147],"(500":[151],"left":[152,185],"500":[154],"right).Genuine":[155],"acceptance":[156],"rate":[157],"for":[160],"comparison.":[162],"experimental":[164],"results":[165],"Cosine":[167],"have":[169,199],"shown":[170],"improvement":[172],"considering":[183],"both":[184],"right":[187],"all":[192],"methods,":[195],"Canny":[196],"Laplace":[198],"proven":[200],"be":[202],"better.":[203]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}